{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        [94, 64, 70],\n",
       "        [68, 92, 90],\n",
       "        [64, 60, 86]]])"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 分数\n",
    "score = np.random.randint(60,100,size=(6,50,3))\n",
    "score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
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      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 0 male 1 female\n",
    "sex = np.random.randint(0,2,size=(6,50,1))\n",
    "sex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(6, 50, 3) (6, 50, 1)\n"
     ]
    },
    {
     "data": {
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       "        ...,\n",
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       "\n",
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       "        ...,\n",
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       "\n",
       "       [[97, 60, 98,  0],\n",
       "        [72, 72, 82,  0],\n",
       "        [79, 78, 89,  1],\n",
       "        ...,\n",
       "        [85, 88, 78,  1],\n",
       "        [78, 63, 97,  0],\n",
       "        [80, 98, 82,  1]],\n",
       "\n",
       "       [[92, 61, 80,  0],\n",
       "        [63, 68, 67,  0],\n",
       "        [98, 84, 92,  0],\n",
       "        ...,\n",
       "        [94, 72, 76,  0],\n",
       "        [73, 98, 62,  1],\n",
       "        [71, 86, 62,  0]],\n",
       "\n",
       "       [[68, 62, 66,  1],\n",
       "        [61, 86, 71,  1],\n",
       "        [91, 80, 89,  1],\n",
       "        ...,\n",
       "        [94, 64, 70,  1],\n",
       "        [68, 92, 90,  0],\n",
       "        [64, 60, 86,  0]]])"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将score 和 sex 拼接成data\n",
    "print(score.shape,sex.shape)\n",
    "data = np.concatenate([score,sex],axis=2)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "cond1 = data[:,:,3] == 1\n",
    "data_female = data[cond1]\n",
    "cond0 = data[:,:,3] == 0\n",
    "data_male = data[cond0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[60 60 60]\n",
      "[60 60 60]\n"
     ]
    }
   ],
   "source": [
    "# 最小分数\n",
    "print(np.min(data_male[:,:3],axis=0))\n",
    "print(np.min(data_female[:,:3],axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[99 99 99]\n",
      "[99 99 99]\n"
     ]
    }
   ],
   "source": [
    "# 最大分数\n",
    "print(np.max(data_male[:,:3],axis=0))\n",
    "print(np.max(data_female[:,:3],axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[79.12142857 78.45       81.32142857]\n",
      "[78.34375 79.925   78.875  ]\n"
     ]
    }
   ],
   "source": [
    "#平均分\n",
    "print(np.mean(data_male[:,:3],axis=0))\n",
    "print(np.mean(data_female[:,:3],axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[79. 78. 83.]\n",
      "[78. 80. 78.]\n"
     ]
    }
   ],
   "source": [
    "# 中位数\n",
    "print(np.median(data_male[:,:3],axis=0))\n",
    "print(np.median(data_female[:,:3],axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[11.87522502 11.6890211  11.63385936]\n",
      "[11.01195196 11.93291142 11.60589828]\n"
     ]
    }
   ],
   "source": [
    "#标准差\n",
    "print(np.std(data_male[:,:3],axis=0))\n",
    "print(np.std(data_female[:,:3],axis=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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